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About
President
Governance
Partner Institutions
Visit
People
Management
Faculty
Postdocs
Visiting Scholars
Administration
Academic Support
Research
Research Groups
Courses
Seminars
Join Us
Faculty
Postdocs
Students
Events
Conferences
Workshops
Forum
Life @ BIMSA
Accommodation
Transportation
Facilities
Tour
News
News
Announcement
Downloads
Qiuzhen College, Tsinghua University
Yau Mathematical Sciences Center, Tsinghua University (YMSC)
Tsinghua Sanya International  Mathematics Forum (TSIMF)
Shanghai Institute for Mathematics and  Interdisciplinary Sciences (SIMIS)
Hetao Institute of Mathematics and Interdisciplinary Sciences
BIMSA > Introduction to Applied High-throughput Biological Data Analysis
Introduction to Applied High-throughput Biological Data Analysis
Next-Generation Sequencing (NGS) has become the cornerstone of modern biology. This course is designed for applied high-throughput biological data analysis, covering RNA-seq, 16S/ITS amplicon sequencing, single-cell RNA-seq, spatial transcriptomics, and beyond. For each data modality, the processes of data acquisition and preprocessing are introduced in detail. The curriculum covers routine analytical methods, such as PCA and Differential Expression Gene (DEG) analysis, alongside advanced techniques like WGCNA and SCENIC. To emphasize hands-on practice, R and Python scripts are provided for half of the course modules to guide students through each workflow. Finally, beyond traditional methodologies, the concluding section introduces novel computational approaches, including ODE-based network modeling.
Lecturer
Ang Dong
Date
13th April ~ 29th June, 2026
Location
Weekday Time Venue Online ID Password
Monday 13:30 - 17:50 A3-1-101 Zoom 16 468 248 1222 BIMSA
Prerequisite
Molecular Biology, R Programming
Reference
Modern Statistics for Modern Biology
Bioinformatics Data Skills
Orchestrating Single-Cell Analysis with Bioconductor
Audience
Advanced Undergraduate , Graduate
Video Public
Yes
Notes Public
Yes
Language
Chinese
Lecturer Intro
Dr.Dong received his education in Biotechnology and Silviculture at Zhejiang A&F University in 2018, then earned his Ph.D. at Beijing Forestry University in 2023. He is broadly interested in the role that network theory plays in paradigm shift in the life sciences, his current research lies at the area of statistical modelling and computer programming. He is working on how to fully utilize existing data to build a network which can analysis the detailed regulatory relationship between genes during the complicated biological process and how to make this idea come true. He also uses computer simulation that allows exploration and verification of design model parameters in multiple scenarios, and helps to further improve and understand the model as well as the complex systems.
Beijing Institute of Mathematical Sciences and Applications
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北京雁栖湖应用数学研究院 101408

Tel. 010-60661855 Tel. 010-60661855
Email. administration@bimsa.cn

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